Summary of the Development of Artificial Intelligence (What are the Development Characteristics of A

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Here are some characteristics of AI development, including: multimodal interaction: AI is not only text or voice interaction, but also visual, tactile and other interactive ways of deep learning and neural networks. In recent years, deep learning and neural networks have made significant progress in the field of AI, and have achieved great success in such fields as image recognition, voice recognition, natural language processing, etc.

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Big data and cloud computing: With the improvement of data generation and storage capacity, big data and cloud computing have become an interdisciplinary infrastructure for the development of artificial intelligence. The development of artificial intelligence needs the expansion of cross cooperation application fields from computer science, mathematics, physics, psychology, neuroscience and other fields. Artificial intelligence continues to expand to more fields, such as automatic driving, medical care, finance, education Entertainment, etc.

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Human machine collaboration: Artificial intelligence is no longer a substitute for humans, but rather collaborates with humans to improve their abilities.

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Edge computing: edge computing is to move computing and data storage to the edge of the network to provide services for users more closely. With the development of the Internet of Things and Industrial Internet, edge computing is increasingly used in the field of artificial intelligence, The interpretability of machine learning services that can achieve lower latency and higher reliability: More and more attention and research have begun to focus on how to enable artificial intelligence systems to interpret their decision-making processes, in order to ensure that artificial intelligence systems are transparent and trustworthy.

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Data augmentation: Data augmentation refers to the random transformation of training data to increase data diversity and improve the generalization ability of models, which has been widely applied in the field of machine learning. General artificial intelligence: Artificial intelligence systems are no longer designed for specific tasks, but can adapt to multiple task ethics and morals. With the increasingly widespread application of artificial intelligence in society, The discussion on the ethics and morality of artificial intelligence has also become increasingly important.

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Multi language support: Artificial intelligence systems have made significant progress in supporting multiple languages, which is crucial for global applications. Engineering deployment: With the development of artificial intelligence technology, the deployment of machine learning models has become increasingly important. Deploying machine learning models requires consideration of factors such as computing resources, network bandwidth, and security.

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At present, cloud computing and distributed storage and computing technology have become the mainstream methods of machine learning deployment